A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Local spatial heteroscedasticity (LOSH)
Abstract In keeping with the Annals of Regional Science 50-year tradition of emphasizing spatial analytic contributions, a new statistic, Hi, is introduced as an extension of the recent work on map pattern analysis using local spatial criteria. In conjunction with local statistics for the mean level of a spatial process, Hi tests for local spatial heteroscedasticity. The statistic measures spatial variability while attempting to avoid the pitfalls of using the non-spatial F test in georeferenced situations. Hi is defined and suitably scaled, and an inferential procedure is given. Three artificial cases are explored: a random pattern, a cluster pattern of high values, and a binary-based cluster. The statistic may be used to identify boundaries of clusters and to describe the nature of heteroscedasticity within clusters.
Local spatial heteroscedasticity (LOSH)
Abstract In keeping with the Annals of Regional Science 50-year tradition of emphasizing spatial analytic contributions, a new statistic, Hi, is introduced as an extension of the recent work on map pattern analysis using local spatial criteria. In conjunction with local statistics for the mean level of a spatial process, Hi tests for local spatial heteroscedasticity. The statistic measures spatial variability while attempting to avoid the pitfalls of using the non-spatial F test in georeferenced situations. Hi is defined and suitably scaled, and an inferential procedure is given. Three artificial cases are explored: a random pattern, a cluster pattern of high values, and a binary-based cluster. The statistic may be used to identify boundaries of clusters and to describe the nature of heteroscedasticity within clusters.
Local spatial heteroscedasticity (LOSH)
Ord, J. Keith (author) / Getis, Arthur (author)
2012
Article (Journal)
English
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